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IntroductionComputational fluid dynamics (CFD) has long been used to model cerebrospinal fluid (CSF) flow in virtual environments, allowing exploration of complex interactions that are difficult to study in vivo. However, CFD faces significant challenges, including its reliance on non-intersecting meshes and the requirement to define boundary conditions—both of which are difficult to obtain in biological systems. Physics-Informed Neural Networks (PINNs), on the other hand, have emerged as a powerful alternative for modeling three-dimensional (3D) flow fields from sparse or incomplete data.Aim of StudyTo reconstruct 3D CSF flow fields using a PINN model trained on planar projection data extracted from CFD simulations in anatomically realistic geometries.MethodA three-dimensional (3D) reconstruction of a canine SAS segment was used, produced from in-vivo real time imaging of the SAS using intravascular high-frequency optical coherence tomography (HF-OCT). CFD simulations of CSF flow within this segment were performed, and planar projection velocity data were extracted. A dedicated PINN model, developed in-house, was trained on this projection data to reconstruct the full 3D velocity field within the sameResultsThe PINN model, initially trained on simple anatomical geometries, yielded results comparable to full CFD simulations. When applied to the complex SAS geometry, the PINN reconstructions achieved less than 10% error relative to CFD predictions.Abstract A247 Figure 1Illustration of multiple arbitraily oriented acquisition planes within a canine subarachnoid space SAS (left) and 3D-reconstruction of simulated CSF flow using a physics informed neural network (PINN) (right). The anatomical data were produced from in vivo real time imaging of the SAS with intravascular HF-OCT[Image Omitted. See PDF.]ConclusionThese findings demonstrate that PINNs can accurately reconstruct complex CSF flow patterns from limited data, offering a promising alternative to traditional CFD by reducing the need for detailed boundary conditions and mesh construction in biological systems.Conflict of InterestNo

IntroductionParticle Image Velocimetry (PIV) is an optical technique used to visualize and quantify fluid flow by tracking the movement of tracer particles within the fluid. High-frequency optical coherence tomography (HF-OCT), with its ~10 μm resolution, offers high-resolution intravascular or intrathecal imaging and may serve as a novel platform for in-situ PIV.Aim of StudyTo evaluate the use of HF-OCT for conducting PIV of cerebrospinal fluid (CSF) and aneurysmal flow patterns in large animal models, both in vivo and in vitro.MethodIn a porcine model, a low-profile OCT catheter was inserted intrathecally, and the CSF was seeded with diluted homologous blood to act as tracer. The catheter was held in position, and a 2–4 second acquisition captured real-time CSF flow, with red blood cells serving as tracers. Separately, a silicone replica of a rabbit aneurysm was integrated into an in-vitro circulatory system operating under physiological conditions. The aneurysm model was filled with saline seeded with diluted bovine blood, and OCT imaging was performed at the aneurysm neck.ResultsAccurate PIV was achieved using HF-OCT data. In vivo imaging of the porcine thecal canal revealed strong lateral CSF motion synchronized with the cardiac cycle and coherent flow structures shaped by surrounding anatomy. In the aneurysm model, flow visualization revealed a distinct recirculation zone resembling a vortex near the aneurysm neck.Abstract A239 Figure 1[Image Omitted. See PDF.]ConclusionIn-vivo PIV using HF-OCT is possible and provides a promising experimental approach for exploring in-situ cerebrovascular and CSF flow dynamics with high resolution.Conflict of InterestNo

IntroductionCerebrospinal fluid (CSF) dynamics within the subarachnoid space are critically influenced by the fine morphology of the arachnoid trabeculae, yet their contribution to CSF flow regulation remains poorly understood.Aim of StudyTo investigate how changes in subarachnoid space porosity affect CSF flow, using a real-time anatomical model derived from in-vivo high-frequency optical coherence tomography (HF-OCT) data.MethodA canine model was used to acquire in-vivo HF-OCT imaging of the subarachnoid space (SAS) microarchitecture, particularly around major blood vessels of the posterior circulation. Imaging through the vessel wall along the vertebrobasilar axis enabled detailed visualization of the trabecular network. From this data, a 3D true anatomical model of the SAS and its trabeculae was reconstructed. Variations in trabecular thickness were applied selectively within the model. High-resolution computational fluid dynamics (CFD) simulations were then used to assess the resulting changes in CSF pressure drop.Abstract A236 Figure 13D reconstruction of a canine subarachnoid space (SAS) segment using OCT images with localized 5% increase in trabecular thickness (the thickened membranes are marked in red)[Image Omitted. See PDF.]ResultsA localized 5% increase in trabecular thickness of membranes distal to the artery resulted in a fivefold increase in pressure drop across the control volume. In contrast, a uniform 5% increase across the entire segment produced only marginal additional changes. The average initial thickness of the trabecular fibers was approximately 50 microns.These findings indicate that specific trabecular structures disproportionately affect CSF flow resistance. Smaller changes in trabecular thickness produced measurable changes in pressure drop but were not found to be significant.ConclusionOur findings suggest that the arachnoid trabeculae play a critical role in modulating CSF dynamics. Alterations in their microstructure may contribute to the pathophysiology of communicating hydrocephalus.Conflict of InterestNo

Background and purposeStudying the imaging and histopathologic characteristics of thrombi in ischemic stroke could provide insights into stroke etiology and ideal treatment strategies. We conducted a systematic review of imaging and histologic characteristics of thrombi in acute ischemic stroke.Materials and methodsWe identified all studies published between January 2005 and December 2015 that reported findings related to histologic and/or imaging characteristics of thrombi in acute ischemic stroke secondary to large vessel occlusion. The five outcomes examined in this study were (1) association between histologic composition of thrombi and stroke etiology; (2) association between histologic composition of thrombi and angiographic outcomes; (3) association between thrombi imaging and histologic characteristics; (4) association between thrombi imaging characteristics and angiographic outcomes; and (5) association between imaging characteristics of thrombi and stroke etiology. A meta-analysis was performed using a random effects model.ResultsThere was no significant difference in the proportion of red blood cell (RBC)-rich thrombi between cardioembolic and large artery atherosclerosis etiologies (OR 1.62, 95% CI 0.1 to 28.0, p=0.63). Patients with a hyperdense artery sign had a higher odds of having RBC-rich thrombi than those without a hyperdense artery sign (OR 9.0, 95% CI 2.6 to 31.2, p<0.01). Patients with a good angiographic outcome had a mean thrombus Hounsfield unit (HU) of 55.1±3.1 compared with a mean HU of 48.4±1.9 for patients with a poor angiographic outcome (mean standard difference 6.5, 95% CI 2.7 to 10.2, p<0.001). There was no association between imaging characteristics and stroke etiology (OR 1.13, 95% CI 0.32 to 4.00, p=0.85).ConclusionsThe hyperdense artery sign is associated with RBC-rich thrombi and improved recanalization rates. However, there was no association between the histopathological characteristics of thrombi and stroke etiology and angiographic outcomes.